Detail kurzu

Advanced Machine Learning Using SAS(R) Viya(R)

EDU Trainings s.r.o.

Popis kurzu

This course teaches you how to optimize the performance of predictive models beyond the basics by implementing various data munging and wrangling techniques. The course continues the development of supervised learning models that begins in the Machine Learning Using SAS Viya course and extends it to ensemble modeling. Running unsupervised learning and semi-supervised learning models are also discussed. In this course, you learn how to do feature engineering and clustering of variables, and how to preprocess nominal variables and detect anomalies. This course uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. Importing and running external models in Model Studio is also discussed, including open source models. SAS Viya automation capabilities at each level of machine learning are also demonstrated, followed by some tips and tricks with Model Studio. The self-study e-learning includes:Annotatable course notes in PDF format. Virtual lab time to practice.

Obsah kurzu

Machine Learning FundamentalsModel Studio review.Classifier performance.Ensemble learning.Feature EngineeringIntroduction to feature engineering.Principal component analysis.Singular value decomposition.Robust principal component analysis.Autoencoders.Transforming categorical variables.Clustering of Variables and ObservationsVariable clustering.Cluster analysis.Anomaly DetectionIntroduction to anomaly detection.Support vector data description.Semi-supervised learning.External Models in Model StudioImporting SAS Enterprise Miner models.Running SAS/STAT or SAS Enterprise Miner models.Running open-source models.Machine Learning AutomationAutomation in SAS Viya.Data preprocessing and feature engineering.Modeling.Automated pipeline creation.Pipeline automation using REST API (self-study).Tips and Tricks with Model StudioManaging metadata.Working with analysis elements.Using the SAS Code node.Interpreting models with extracted features.Scoring unsupervised learning models.

Cílová skupina

Advanced machine learning modelers who use Model Studio
Certifikát Na dotaz.
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